Prosite and UCSC Genome Browser Exercise 3. Protein motifs and Prosite

Prosite and Prosite and UCSC Genome UCSC Genome

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Exercise 3Exercise 3

Protein motifsProtein motifs and and

Prosite Prosite

Turning information into knowledgeTurning information into knowledge

The outcome of a sequencing project is The outcome of a sequencing project is masses of raw datamasses of raw data

The challenge is to turn this The challenge is to turn this raw data into raw data into biological knowledgebiological knowledge

A valuable tool for this challenge is an A valuable tool for this challenge is an automated diagnostic pipe through which automated diagnostic pipe through which newly determined sequences can be newly determined sequences can be streamlinedstreamlined

From sequence to functionFrom sequence to function

Nature tends to innovate rather than inventNature tends to innovate rather than invent Proteins are composed of functional Proteins are composed of functional

elements: domains and motifselements: domains and motifs DomainsDomains are structural units that carry out a are structural units that carry out a

certain functioncertain function The same domains are The same domains are

shared between different shared between different proteinsproteins

MotifsMotifs are shorter are shorter sequences with certainsequences with certainbiological activitybiological activity

What is a motif?What is a motif?

A sequence motifA sequence motif = a certain sequence = a certain sequence that is widespread and conjectured to that is widespread and conjectured to have biological significancehave biological significance

Examples:Examples:KDELKDEL – ER-lumen retention signal – ER-lumen retention signalPKKKRKVPKKKRKV – an NLS (nuclear localization – an NLS (nuclear localization signal)signal)

More loosely defined motifsMore loosely defined motifs

KDEL (usually)KDEL (usually)++

HDEL (rarely) HDEL (rarely) ==

[HK]-D-E-L:[HK]-D-E-L:H H oror K at the first position K at the first position

This is called a pattern (in Biology), or a This is called a pattern (in Biology), or a regular expression (in computer science)regular expression (in computer science)

Syntax of a patternSyntax of a pattern

Example:Example: W-x(9,11)-[FYV]-[FYW]-x(6,7)-[GSTNE]W-x(9,11)-[FYV]-[FYW]-x(6,7)-[GSTNE]

PatternsPatterns

W-x(9,11)-[FYV]-[FYW]-x(6,7)-[GSTNE]W-x(9,11)-[FYV]-[FYW]-x(6,7)-[GSTNE]

Any amino-acid, between 9-11

times

F or Y or

V

WOPLASDFGYVWPPPLAWSROPLASDFGYVWPPPLAWSWOPLASDFGYVWPPPLSQQQ

Patterns - syntaxPatterns - syntax

The standard IUPAC one-letter codes. The standard IUPAC one-letter codes. ‘‘x’x’ : any amino acid. : any amino acid. ‘‘[]’[]’ : residues allowed at the position. : residues allowed at the position. ‘‘{}’{}’ : residues forbidden at the position. : residues forbidden at the position. ‘‘()’()’ : repetition of a pattern element are indicated in : repetition of a pattern element are indicated in

parenthesis. X(n) or X(n,m) to indicate the number or parenthesis. X(n) or X(n,m) to indicate the number or range of repetition. range of repetition.

‘‘-’-’ : separates each pattern element. : separates each pattern element. ‘‹’‘‹’ : indicated a N-terminal restriction of the pattern. : indicated a N-terminal restriction of the pattern. ‘›’‘›’ : indicated a C-terminal restriction of the pattern. : indicated a C-terminal restriction of the pattern. ‘‘.’.’ : the period ends the pattern. : the period ends the pattern.

Profile-pattern-consensusProfile-pattern-consensus

AAAACCTTTTGG

AAAAGGTTCCGG

CCAACCTTTTCC

1122334455

AA0.660.66110000..

TT00000011..

CC0.330.33000.660.6600..

GG00000.330.3300..

AAAACCTTTTGG

]AC-[A-[GC]-T-[TC]-[GC]

multiple alignment

consensus

pattern

profile

NNAANNTTNNNN

http://www.expasy.ch/http://www.expasy.ch/prositeprosite//

PrositeProsite

A method for determining the function of A method for determining the function of uncharacterized translated protein uncharacterized translated protein sequencessequences

Database of annotated protein families Database of annotated protein families and functional sites as well as associated and functional sites as well as associated patterns and profiles to identify thempatterns and profiles to identify them

PrositeProsite Entries are represented with Entries are represented with patternspatterns or or

profilesprofiles

pattern

1122334455

AA0.660.66110000..

TT00000011..

CC0.330.33000.660.6600..

GG00000.330.3300..

profile

]AC-[A-[GC]-T-[TC]-[GC]

Profiles are used in Prosite when the motif is relatively Profiles are used in Prosite when the motif is relatively divergent and it is difficult to represent as a patterndivergent and it is difficult to represent as a pattern

Scanning PrositeScanning Prosite

Query: sequence

Query: pattern

Result: all patterns found in sequence

Result: all sequences which adhere to this pattern

prosite sequence queryprosite sequence query

Prosite profileProsite profile

Prosite profile Prosite profile sequence logo sequence logo

Sequence logoSequence logo

WebLogoWebLogo

http://weblogo.berkeley.edu/logo.cgi

Searching Prosite with a sequenceSearching Prosite with a sequence

Patterns with a high probability of Patterns with a high probability of occurrenceoccurrence

Entries describing commonly found postEntries describing commonly found post--translational modifications or compositionally translational modifications or compositionally biased regions.biased regions.

Found in the majority of known protein Found in the majority of known protein sequences sequences

High probability of occurrenceHigh probability of occurrence

Searching Prosite with a patternSearching Prosite with a pattern

prosite pattern queryprosite pattern query

Searching Prosite with a Prosite ACSearching Prosite with a Prosite AC

UCSC UCSC Genome Browser Genome Browser

UCSC Genome BrowserUCSC Genome Browser

UCSC Genome BrowserUCSC Genome Browser

Reset all settings of

previous user

UCSC Genome Browser - GatewayUCSC Genome Browser - Gateway

UCSC Genome Browser - GatewayUCSC Genome Browser - Gateway

UCSC Genome Browser - GatewayUCSC Genome Browser - Gateway

UCSC Genome Browser query resultsUCSC Genome Browser query results

UCSC Genome Browser UCSC Genome Browser Annotation tracksAnnotation tracks

Vertebrate conservation

mRNA (GenBank)

RefSeq

UCSC Genes

Base position

Single species compared

SNPs

Repeats

Direction oftranscription (<)

CDS

Intron

UTR

USCS GeneUSCS Gene

UCSC Genome Browser - movementUCSC Genome Browser - movement

Zoom x3 + Center

UCSC Genome Browser – UCSC Genome Browser – Base viewBase view

Annotation track optionsAnnotation track options

dense

squish

full

pack

Annotation track optionsAnnotation track optionsAnother option totoggle between

‘pack’ and ‘dense’view is to click on

the track title

Sickle-cell anemia distr.

Malariadistr.

BLATBLAT

BLAT = BBLAT = Blast-last-LLike ike AAlignment lignment TTool ool BLAT is designed to find similarity of BLAT is designed to find similarity of >95% on >95% on

DNADNA, , >80% for protein>80% for protein Rapid search by indexing entire genome.Rapid search by indexing entire genome.Good for:Good for:1.1. Finding genomic coordinates of cDNAFinding genomic coordinates of cDNA2.2. Determining exons/intronsDetermining exons/introns3.3. Finding human (or chimp, dog, cow…) Finding human (or chimp, dog, cow…)

homologs of another vertebrate sequencehomologs of another vertebrate sequence4.4. Find upstream regulatory regionsFind upstream regulatory regions

BLAT on UCSC Genome BrowserBLAT on UCSC Genome Browser

BLAT on UCSC Genome BrowserBLAT on UCSC Genome Browser

BLAT ResultsBLAT Results

BLAT ResultsBLAT Results

Match

Non-Match(mismatch/indel)

Indel boundaries

BLAT ResultsBLAT Results

BLAT Results on the browserBLAT Results on the browser

Getting Getting DNADNA sequence of region sequence of region

Getting Getting DNADNA sequence of region sequence of region